Let MSA defines mean sum of squares due to factor A and MSE defines mean sum of squares dueto error. If the null hypothesis of ANOVA for one way classification is not true, then $$\frac{E(MSA)}{E(MSE)}$$ is:

A

equal to -1

B

more than 1

C

equal to 1

D

less than 1